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These are the user uploaded subtitles that are being translated: 1 00:00:01,300 --> 00:00:04,670 Every 17 minutes in America, 2 00:00:04,670 --> 00:00:08,540 someone is killed by a gun. 3 00:00:08,540 --> 00:00:12,740 It's a wave of violence that political debate 4 00:00:12,750 --> 00:00:14,880 can't seem to stop. 5 00:00:14,880 --> 00:00:18,380 Can science point the way forward 6 00:00:18,390 --> 00:00:22,020 by pinpointing how the shootings spread, 7 00:00:22,020 --> 00:00:26,660 predicting gun crimes before they happen, 8 00:00:26,660 --> 00:00:30,330 and uncovering how guns infect our minds? 9 00:00:32,130 --> 00:00:36,470 Is this an epidemic that can be cured? 10 00:00:36,470 --> 00:00:40,110 Could gun crime be a virus? 11 00:00:44,180 --> 00:00:51,280 Space, time, life itself, 12 00:00:51,280 --> 00:00:53,890 the secrets of the cosmos lie 13 00:00:53,890 --> 00:00:56,820 through the wormhole. 14 00:00:56,820 --> 00:00:59,420 Captions by vitac... www.Vitac.Com 15 00:00:59,430 --> 00:01:02,060 captions paid for by discovery communications 16 00:01:07,500 --> 00:01:14,170 if gun violence is a disease, we are suffering mightily. 17 00:01:14,170 --> 00:01:18,180 In Chicago, where shootings on a summer weekend 18 00:01:18,180 --> 00:01:20,710 soar into the double digits. 19 00:01:20,710 --> 00:01:23,880 In Newtown, where 20 children 20 00:01:23,880 --> 00:01:26,480 never came home from school. 21 00:01:26,490 --> 00:01:27,890 In Orlando, 22 00:01:27,890 --> 00:01:31,460 where a night of dancing became a bloodbath. 23 00:01:31,460 --> 00:01:32,820 Every day, 24 00:01:32,830 --> 00:01:37,060 new holes are opened up in some family's life. 25 00:01:37,060 --> 00:01:43,130 Is gun control the answer, or is it safer to carry one? 26 00:01:43,140 --> 00:01:47,910 The answer may come, not from politicians, 27 00:01:47,910 --> 00:01:49,670 but from scientists, 28 00:01:49,680 --> 00:01:52,010 who are tracking the spread of gun crime 29 00:01:52,010 --> 00:01:54,350 like a biological pandemic. 30 00:01:56,220 --> 00:01:58,120 Reports of a school shooting in progress 31 00:01:58,120 --> 00:02:00,020 are coming out of Colorado today. 32 00:02:00,020 --> 00:02:02,850 They started shooting everyone in the cafeteria, 33 00:02:02,860 --> 00:02:05,720 and then you could hear them laughing and running upstairs. 34 00:02:05,730 --> 00:02:10,800 Since columbine, the heartbreak has been broadcast live. 35 00:02:10,800 --> 00:02:14,630 Since Orlando, it's been screened. 36 00:02:14,630 --> 00:02:17,000 The names have been running together. 37 00:02:17,000 --> 00:02:19,540 It's a flood of data. 38 00:02:19,540 --> 00:02:22,310 How do we understand it? 39 00:02:22,310 --> 00:02:24,610 Sherry towers is a statistician. 40 00:02:24,610 --> 00:02:28,580 In her work, streams of data tell stories. 41 00:02:28,580 --> 00:02:29,980 One of the things that I've noticed 42 00:02:29,980 --> 00:02:31,180 as I've been sitting here 43 00:02:31,180 --> 00:02:33,620 is that, once people lock their bikes there, 44 00:02:33,620 --> 00:02:35,650 they tend to walk underneath that tree 45 00:02:35,660 --> 00:02:37,890 and go to the path. 46 00:02:37,890 --> 00:02:45,030 - Bicycle, lock, tree, repeat. - Sherry can make a prediction. 47 00:02:45,030 --> 00:02:49,770 Soon, bikers will wear a path in the grass. 48 00:02:49,770 --> 00:02:51,770 We can use mathematical and statistical models 49 00:02:51,770 --> 00:02:53,540 to study far more complex patterns 50 00:02:53,540 --> 00:02:56,510 than just the ones we're seeing on this school campus today. 51 00:02:56,510 --> 00:02:58,810 For instance, these models can be used to predict 52 00:02:58,810 --> 00:03:01,310 the spread of disease within a population. 53 00:03:01,310 --> 00:03:02,480 We can use these models 54 00:03:02,480 --> 00:03:04,850 to try to forecast trends in the stock market. 55 00:03:04,850 --> 00:03:07,690 We can also use these models to examine earthquakes 56 00:03:07,690 --> 00:03:10,620 and try to predict when and where there will be aftershocks. 57 00:03:13,160 --> 00:03:16,690 But one day in 2014, Sherry's safe world 58 00:03:16,700 --> 00:03:21,030 of spreadsheets and stats came unmoored. 59 00:03:21,030 --> 00:03:23,700 She was heading to a meeting at Purdue university 60 00:03:23,700 --> 00:03:25,900 when the event was canceled. 61 00:03:28,170 --> 00:03:31,510 A student had been shot on campus. 62 00:03:31,510 --> 00:03:33,610 I realized that, that was the third school shooting 63 00:03:33,610 --> 00:03:36,050 I had heard about in approximately a 10-day period. 64 00:03:36,050 --> 00:03:37,450 And I wondered to myself 65 00:03:37,450 --> 00:03:39,180 if this was just a statistical fluke 66 00:03:39,190 --> 00:03:42,750 or whether there was other patterns involved. 67 00:03:42,760 --> 00:03:45,920 Then, Sherry had a radical idea. 68 00:03:45,930 --> 00:03:49,790 Could the media itself be the mechanism of transmission? 69 00:03:49,800 --> 00:03:54,330 Could stories about shootings actually lead to more shootings, 70 00:03:54,330 --> 00:03:57,370 triggering an epidemic? 71 00:03:57,370 --> 00:03:59,470 We decided to focus on gun tragedies 72 00:03:59,470 --> 00:04:01,410 that get the most media attention, 73 00:04:01,410 --> 00:04:04,840 and those are school shootings and mass killings. 74 00:04:04,840 --> 00:04:07,050 Sherry's team went story by story 75 00:04:07,050 --> 00:04:11,220 and broke the events into discrete pieces of data... 76 00:04:11,220 --> 00:04:19,090 Type of shooting, map location, date, and time. 77 00:04:19,090 --> 00:04:21,860 It was the largest, most comprehensive survey 78 00:04:21,860 --> 00:04:23,960 of its kind. 79 00:04:23,960 --> 00:04:26,730 Was each shooting an isolated event? 80 00:04:31,100 --> 00:04:36,470 With all the data in, Sherry was able to isolate a pattern. 81 00:04:36,480 --> 00:04:39,840 It didn't matter where an event occurred. 82 00:04:39,850 --> 00:04:42,680 The important variable was when. 83 00:04:42,680 --> 00:04:45,220 What we found was, there is very strong evidence 84 00:04:45,220 --> 00:04:47,190 of clustering in time. 85 00:04:47,190 --> 00:04:49,150 When there is an event that occurs, 86 00:04:49,160 --> 00:04:50,460 one of these gun tragedies 87 00:04:50,460 --> 00:04:52,720 tends to trigger a similar tragedy 88 00:04:52,730 --> 00:04:54,430 in the very near future. 89 00:04:54,430 --> 00:04:56,030 And this bunching together in time 90 00:04:56,030 --> 00:04:59,300 is actually the hallmark of contagion. 91 00:04:59,300 --> 00:05:01,530 We typically use the word "contagion" 92 00:05:01,530 --> 00:05:03,840 to describe the spread of diseases, 93 00:05:03,840 --> 00:05:08,740 but Sherry says it also applies to mass shootings. 94 00:05:08,740 --> 00:05:11,440 It appears the gun violence really does spread 95 00:05:11,440 --> 00:05:13,540 like a contagious disease. 96 00:05:13,550 --> 00:05:15,850 Unlike influenza, that spreads by direct, 97 00:05:15,850 --> 00:05:17,520 person-to-person contact, 98 00:05:17,520 --> 00:05:21,420 the medium for spreading the contagion is media itself. 99 00:05:24,620 --> 00:05:27,330 And, as with a biological virus, 100 00:05:27,330 --> 00:05:30,190 Sherry's data show there is a definite period 101 00:05:30,200 --> 00:05:35,500 during which any one incident of gun violence remains contagious. 102 00:05:35,500 --> 00:05:36,970 What we find is that, 103 00:05:36,970 --> 00:05:40,100 the contagious period seems to last around 13 days, 104 00:05:40,110 --> 00:05:42,570 which also seems to be, approximately, 105 00:05:42,580 --> 00:05:45,040 the same time period of the attention span 106 00:05:45,050 --> 00:05:46,810 that's given to these high-profile shootings, 107 00:05:46,810 --> 00:05:48,550 like, for instance, the Newtown tragedy 108 00:05:48,550 --> 00:05:51,180 or the San Bernardino tragedy. 109 00:05:51,180 --> 00:05:56,590 13 days... One famously unlucky number. 110 00:05:56,590 --> 00:06:00,930 Sherry hopes she'll never make another discovery like it. 111 00:06:00,930 --> 00:06:04,330 This is, by far, the hardest study, emotionally, 112 00:06:04,330 --> 00:06:06,200 that we've ever undertaken. 113 00:06:06,200 --> 00:06:09,300 You're reading the details about how children have gotten killed, 114 00:06:09,300 --> 00:06:11,670 and you realize that these are entire families 115 00:06:11,670 --> 00:06:14,410 who aren't here anymore. 116 00:06:14,410 --> 00:06:16,470 Sherry believes that, as long as the media 117 00:06:16,480 --> 00:06:19,640 keeps giving mass shootings wall-to-wall coverage, 118 00:06:19,650 --> 00:06:22,180 the gun virus will continue to spread 119 00:06:22,180 --> 00:06:25,650 and claim even more victims 120 00:06:25,650 --> 00:06:29,390 unless someone intervenes. 121 00:06:29,390 --> 00:06:30,720 Shots fired. 122 00:06:30,720 --> 00:06:33,120 Mass shootings are the most visible aspect 123 00:06:33,130 --> 00:06:36,660 of America's problem with gun violence. 124 00:06:36,660 --> 00:06:39,830 But vastly more Americans are killed in isolated shootings 125 00:06:39,830 --> 00:06:42,030 on city streets. 126 00:06:42,040 --> 00:06:43,230 And many of these killings 127 00:06:43,240 --> 00:06:46,440 receive little or no media coverage. 128 00:06:46,440 --> 00:06:49,540 But renowned epidemiologist Gary Slutkin 129 00:06:49,540 --> 00:06:53,780 thinks they, too, bear the hallmarks of a virus. 130 00:06:53,780 --> 00:06:56,550 Gary made his name by fighting contagious diseases 131 00:06:56,550 --> 00:06:58,280 all around the world. 132 00:06:58,280 --> 00:07:00,690 But when he finally returned to Chicago, 133 00:07:00,690 --> 00:07:02,520 he realized his hometown 134 00:07:02,520 --> 00:07:05,190 harbored an epidemic of a different kind. 135 00:07:05,190 --> 00:07:08,690 When I began to look at violence in Chicago, 136 00:07:08,700 --> 00:07:10,600 I didn't really know very much about it. 137 00:07:10,600 --> 00:07:15,070 But I did ask, first, to see the charts and graphs and maps, 138 00:07:15,070 --> 00:07:19,770 and the data on it looked exactly like the epidemic maps 139 00:07:19,770 --> 00:07:22,610 that I had been working with in all these other problems. 140 00:07:22,610 --> 00:07:26,940 To Gary's trained eye, the clustering of gun crimes 141 00:07:26,950 --> 00:07:29,680 resembled the way a contagious disease 142 00:07:29,680 --> 00:07:32,820 sweeps through densely populated areas. 143 00:07:32,820 --> 00:07:36,550 He'd seen cholera do this in refugee camps in Somalia 144 00:07:36,560 --> 00:07:38,690 during the 1990s. 145 00:07:38,690 --> 00:07:41,230 So, what we have here is a representation 146 00:07:41,230 --> 00:07:42,890 of a refugee camp. 147 00:07:42,900 --> 00:07:47,060 The white chips here are representing the population, 148 00:07:47,070 --> 00:07:49,730 and the red, a person with cholera. 149 00:07:49,740 --> 00:07:52,170 And when the infection comes, 150 00:07:52,170 --> 00:07:55,970 it can spread from one person to another. 151 00:08:01,580 --> 00:08:03,950 Stopping cholera isn't complicated. 152 00:08:03,950 --> 00:08:06,220 A strict regimen of washing hands, 153 00:08:06,220 --> 00:08:09,220 boiling water, and quarantine will do it. 154 00:08:09,220 --> 00:08:14,190 But Gary struggled to get these practices adopted in Somalia 155 00:08:14,190 --> 00:08:17,860 because the refugees were suspicious of outsiders. 156 00:08:17,860 --> 00:08:20,570 Then, Gary had an inspiration... 157 00:08:20,570 --> 00:08:25,570 He could hire refugees and train them as health workers. 158 00:08:25,570 --> 00:08:27,410 These locals successfully interrupted 159 00:08:27,410 --> 00:08:29,510 the spread of the disease 160 00:08:29,510 --> 00:08:34,980 because they had what Gary did not... 161 00:08:34,980 --> 00:08:38,120 Street cred. 162 00:08:38,120 --> 00:08:41,850 In Chicago, Gary saw a city repeating the mistake 163 00:08:41,850 --> 00:08:44,420 he'd once made himself... 164 00:08:44,420 --> 00:08:46,760 Fighting an outbreak with outsiders 165 00:08:46,760 --> 00:08:48,060 who weren't trusting. 166 00:08:50,430 --> 00:08:51,830 The cops pulled up, and they left. 167 00:08:51,830 --> 00:08:52,830 They're scared. 168 00:08:52,830 --> 00:08:54,330 They're scared of the community. 169 00:08:54,330 --> 00:08:58,940 So, Gary founded an organization called "cure violence" 170 00:08:58,940 --> 00:09:03,710 with the mission to hire and train trusted local aid workers. 171 00:09:03,710 --> 00:09:06,710 He calls them "the interrupters." 172 00:09:06,710 --> 00:09:08,580 Almost all of them know the violence 173 00:09:08,580 --> 00:09:10,510 of the streets firsthand. 174 00:09:10,520 --> 00:09:13,380 Well, I've been shot five times, you know, 175 00:09:13,390 --> 00:09:14,850 on different occasions. 176 00:09:14,850 --> 00:09:17,490 The man that was watching us got shot in his head. 177 00:09:17,490 --> 00:09:18,820 I was part of the violence. 178 00:09:18,830 --> 00:09:20,930 Now, I'm part of the solution. 179 00:09:20,930 --> 00:09:22,990 Because of who they are, 180 00:09:23,000 --> 00:09:25,830 interrupters can go where police cannot. 181 00:09:25,830 --> 00:09:27,770 They don't carry handcuffs 182 00:09:27,770 --> 00:09:30,170 and they don't serve search warrants. 183 00:09:30,170 --> 00:09:33,800 Instead, they carry a simple message... 184 00:09:33,810 --> 00:09:37,210 You don't need a gun to settle an argument. 185 00:09:37,210 --> 00:09:38,580 Crazy, man. 186 00:09:38,580 --> 00:09:40,040 You two guys, man, y'all been around here 187 00:09:40,050 --> 00:09:41,650 on a lot of bull, both of y'all. 188 00:09:41,650 --> 00:09:45,420 Robbing people, breaking in windows, all kinds of stuff. 189 00:09:45,420 --> 00:09:46,850 Don't get it all twisted. 190 00:09:46,850 --> 00:09:49,620 Once upon a time, this man was out here too. 191 00:09:49,620 --> 00:09:52,320 Through the interrupters, Gary keeps the focus 192 00:09:52,330 --> 00:09:54,090 where he thinks it belongs... 193 00:09:54,090 --> 00:09:57,700 On preventing disease, not punishing crimes. 194 00:09:57,700 --> 00:10:00,330 So, Jacob, you from this community. 195 00:10:00,330 --> 00:10:02,030 You're going to be hearing gunshots tonight? 196 00:10:02,040 --> 00:10:03,830 Probably, 'cause if you tell 197 00:10:03,840 --> 00:10:06,740 for whatever I did yesterday, it's just a cycle. 198 00:10:06,740 --> 00:10:08,840 If you want to use violence and shoot somebody as a way 199 00:10:08,840 --> 00:10:10,110 to solve your differences, 200 00:10:10,110 --> 00:10:11,940 we trying to say that's not the way to go 201 00:10:11,940 --> 00:10:13,740 'cause you can't take back a life. 202 00:10:13,750 --> 00:10:17,110 It's a simple, but revolutionary, approach, 203 00:10:17,120 --> 00:10:19,650 and it has shown dramatic results. 204 00:10:19,650 --> 00:10:20,950 We started in February. 205 00:10:20,950 --> 00:10:24,220 By march, it was already 67% down. 206 00:10:24,220 --> 00:10:25,790 It was amazing. 207 00:10:25,790 --> 00:10:28,260 There was this park across the street that they'd never use. 208 00:10:28,260 --> 00:10:30,760 Now, their kids are playing there. 209 00:10:30,760 --> 00:10:32,600 The epidemic's no longer there. 210 00:10:35,970 --> 00:10:38,170 Gary has now rolled out "cured violence" 211 00:10:38,170 --> 00:10:41,310 in locations across the country. 212 00:10:41,310 --> 00:10:45,780 On average, the program has reduced shootings by 44% 213 00:10:45,780 --> 00:10:51,320 and killings by up to 56% in the neighborhoods it targets. 214 00:10:51,320 --> 00:10:54,520 It's an approach born from medical techniques. 215 00:10:54,520 --> 00:10:58,360 To Gary, its success proves gun crime 216 00:10:58,360 --> 00:11:00,490 is no different from a virus. 217 00:11:03,460 --> 00:11:07,830 You can't see gun crime under a microscope, 218 00:11:07,830 --> 00:11:10,600 but if it spreads like a virus, 219 00:11:10,600 --> 00:11:13,800 if we can fight it like we fight a virus, 220 00:11:13,810 --> 00:11:16,670 maybe we need to stop thinking about gun crime 221 00:11:16,680 --> 00:11:18,110 as a political issue 222 00:11:18,110 --> 00:11:21,680 and start treating it as a medical issue. 223 00:11:21,680 --> 00:11:24,520 Some researchers already are. 224 00:11:24,520 --> 00:11:27,850 They've discovered a new way to predict shootings 225 00:11:27,850 --> 00:11:29,290 and to stop them. 226 00:11:33,220 --> 00:11:37,120 Every virus spreads in its own unique way. 227 00:11:37,120 --> 00:11:39,660 Mosquitos spread malaria. 228 00:11:39,660 --> 00:11:41,890 The common cold relies on the sneeze 229 00:11:41,890 --> 00:11:45,130 to spread its germs through the air. 230 00:11:45,130 --> 00:11:48,130 On the Internet, memes go viral when they spread 231 00:11:48,130 --> 00:11:52,540 from person to person across a social network. 232 00:11:52,540 --> 00:11:56,370 If we're going to stem the epidemic of gun violence, 233 00:11:56,370 --> 00:12:00,110 we have to discover the precise means of its transmission. 234 00:12:02,180 --> 00:12:04,510 In Chicago, the police department 235 00:12:04,520 --> 00:12:06,480 is trying to do just that 236 00:12:06,480 --> 00:12:10,250 by launching a high-tech and highly controversial program 237 00:12:10,250 --> 00:12:12,690 to reduce gun crime. 238 00:12:12,690 --> 00:12:16,060 This is the heart of the operation. 239 00:12:16,060 --> 00:12:21,000 It connects to 29,000 surveillance cameras. 240 00:12:21,000 --> 00:12:25,000 It has microphones to record gunshots in real time, 241 00:12:25,000 --> 00:12:27,200 and the brain behind all of this 242 00:12:27,210 --> 00:12:29,410 is an algorithm designed to predict 243 00:12:29,410 --> 00:12:32,380 who is going to be the next victim of a gun crime 244 00:12:32,380 --> 00:12:35,010 before the crime happens. 245 00:12:35,010 --> 00:12:40,450 It was developed by Illinois tech professor Miles Wernick. 246 00:12:40,450 --> 00:12:41,880 The algorithm tries to see, 247 00:12:41,890 --> 00:12:44,550 how many times have you been shot recently, 248 00:12:44,560 --> 00:12:47,420 how many times have you been arrested on things 249 00:12:47,430 --> 00:12:49,030 like weapons charges. 250 00:12:49,030 --> 00:12:51,390 And all of those play into a pattern, 251 00:12:51,400 --> 00:12:54,000 which turns out to be very accurate 252 00:12:54,000 --> 00:12:56,300 in predicting a person's risk. 253 00:12:56,300 --> 00:12:59,040 Miles developed his algorithm from one he'd used 254 00:12:59,040 --> 00:13:03,940 to detect the spread of cancer cells in MRI scans. 255 00:13:03,940 --> 00:13:07,040 But Chicago pd deputy chief Jonathan Lewin 256 00:13:07,050 --> 00:13:11,410 has used it to develop a politically charged heat list... 257 00:13:11,420 --> 00:13:13,550 The 400 people in Chicago 258 00:13:13,550 --> 00:13:17,790 most likely to be involved in violent crime. 259 00:13:17,790 --> 00:13:19,760 So, we were wondering, could we look at 260 00:13:19,760 --> 00:13:21,960 person-based prediction methods, 261 00:13:21,960 --> 00:13:25,260 and could we look at a way to develop a risk score 262 00:13:25,260 --> 00:13:27,330 for a specific person's likelihood 263 00:13:27,330 --> 00:13:29,500 for becoming involved in future gun crimes? 264 00:13:29,500 --> 00:13:31,530 This is a subject who, as you can see, 265 00:13:31,540 --> 00:13:33,340 was first arrested when he was 13. 266 00:13:33,340 --> 00:13:35,000 He was 14 in that picture. 267 00:13:35,010 --> 00:13:38,170 See, he's 15. 268 00:13:38,180 --> 00:13:40,410 And this, we see too often. 269 00:13:40,410 --> 00:13:42,110 The subject ended up being killed... 270 00:13:42,110 --> 00:13:44,010 Fatal, multiple gunshot wounds. 271 00:13:44,020 --> 00:13:47,120 Everything we're doing is trying to prevent this. 272 00:13:47,120 --> 00:13:50,120 Is the heat list government overreach, 273 00:13:50,120 --> 00:13:52,590 an invasion of privacy? 274 00:13:52,590 --> 00:13:54,590 Or can such tightly targeted policing 275 00:13:54,590 --> 00:13:57,960 actually stop the spread of gun violence? 276 00:13:57,960 --> 00:14:01,260 Yale professor and Chicago native Andrew Papachristos 277 00:14:01,270 --> 00:14:03,900 believes we need more and better data 278 00:14:03,900 --> 00:14:07,700 to predict and prevent the spread of urban crime. 279 00:14:07,710 --> 00:14:10,710 His social statistics work was the inspiration 280 00:14:10,710 --> 00:14:13,310 for Chicago's current program. 281 00:14:13,310 --> 00:14:16,480 So, really, my stock and trade is dealing with big data sets, 282 00:14:16,480 --> 00:14:17,750 data sets like arrest records, 283 00:14:17,750 --> 00:14:19,750 immunization records, census records, 284 00:14:19,750 --> 00:14:22,750 survey records, and pulling them all together. 285 00:14:22,750 --> 00:14:25,890 So, when I was growing up in Chicago, there were 800, 900, 286 00:14:25,890 --> 00:14:27,890 nearing 1,000 homicides a year. 287 00:14:27,890 --> 00:14:30,390 And kids all around me were getting pulled into gangs, 288 00:14:30,390 --> 00:14:31,960 other types of stuff. 289 00:14:31,960 --> 00:14:34,260 Still, I've never had anybody pull a gun on me. 290 00:14:34,270 --> 00:14:35,300 I've never been shot at. 291 00:14:35,300 --> 00:14:37,470 The question is, "why?" 292 00:14:37,470 --> 00:14:41,000 Andrew doesn't believe he just got lucky. 293 00:14:41,010 --> 00:14:43,310 His research shows that gun crime 294 00:14:43,310 --> 00:14:46,010 is tied to limited networks of people... 295 00:14:46,010 --> 00:14:49,550 Far smaller networks than you might expect. 296 00:14:49,550 --> 00:14:53,720 And you don't have to be a criminal to be a victim. 297 00:14:53,720 --> 00:14:55,950 Jonylah Watkins was just six months old 298 00:14:55,950 --> 00:14:57,820 when she was shot to death. 299 00:14:57,820 --> 00:15:00,060 She was lying in the back seat of a car 300 00:15:00,060 --> 00:15:02,930 while her father changed her diaper. 301 00:15:02,930 --> 00:15:04,460 She was so innocent. 302 00:15:04,460 --> 00:15:06,930 Her murder looked truly random, and I was interested 303 00:15:06,930 --> 00:15:09,170 to see how random it actually was. 304 00:15:09,170 --> 00:15:11,970 Investigators learned Jonylah's father 305 00:15:11,970 --> 00:15:14,500 was the target of the attack. 306 00:15:14,510 --> 00:15:16,940 To the media, her death was a tragic case 307 00:15:16,940 --> 00:15:20,810 of being in the wrong place at the wrong time. 308 00:15:20,810 --> 00:15:23,910 But as a statistician, Andrew wanted to know 309 00:15:23,920 --> 00:15:27,320 whether Jonylah's death could have been predicted. 310 00:15:27,320 --> 00:15:30,920 Jonylah didn't have almost any of the risk factors 311 00:15:30,920 --> 00:15:32,660 that we usually look at in these models... 312 00:15:32,660 --> 00:15:34,760 Being young, being male, 313 00:15:34,760 --> 00:15:36,030 living in a particular neighborhood, 314 00:15:36,030 --> 00:15:37,430 being part of a street gang. 315 00:15:37,430 --> 00:15:40,000 But what those really tell you are about aggregate risks. 316 00:15:40,000 --> 00:15:42,400 The vast majority of people with those attributes, 317 00:15:42,400 --> 00:15:45,570 they never shoot anybody nor do they ever get shot. 318 00:15:45,570 --> 00:15:48,240 To find Jonylah's risk factor, 319 00:15:48,240 --> 00:15:51,640 Andrew peered into the network of people around her 320 00:15:51,640 --> 00:15:56,450 using a forensic tool called "social network analysis." 321 00:15:58,620 --> 00:16:01,280 It measures relationships between people, 322 00:16:01,290 --> 00:16:04,550 counting their number and their strength. 323 00:16:04,560 --> 00:16:07,220 Who were Jonylah's parents? 324 00:16:07,230 --> 00:16:11,090 Who were their friends and their friends' friends? 325 00:16:11,100 --> 00:16:14,800 All of those connections carry risk factors. 326 00:16:14,800 --> 00:16:17,500 So, one of the variables that really helps you identify 327 00:16:17,500 --> 00:16:20,040 who's at risk, who's a potential victim, 328 00:16:20,040 --> 00:16:22,240 is exposure to violence. 329 00:16:22,240 --> 00:16:24,470 Even if you're not directly engaging 330 00:16:24,480 --> 00:16:27,440 in these sorts of incidents, but people around you are, 331 00:16:27,450 --> 00:16:30,510 it can increase your individual probability of getting shot 332 00:16:30,510 --> 00:16:33,480 upwards to 500% to 900%. 333 00:16:33,480 --> 00:16:37,650 For Jonylah, the greatest risks stemmed from her father. 334 00:16:37,660 --> 00:16:42,290 He had been shot in the past, and almost 40% of his associates 335 00:16:42,290 --> 00:16:44,890 had been victims of violence. 336 00:16:44,900 --> 00:16:47,930 Statistics don't assign blame to anyone, 337 00:16:47,930 --> 00:16:50,300 but mathematically speaking, 338 00:16:50,300 --> 00:16:53,040 anyone belonging to her father's social network 339 00:16:53,040 --> 00:16:57,540 faced dramatically higher risks. 340 00:16:57,540 --> 00:16:59,880 If her father is literally living in a world 341 00:16:59,880 --> 00:17:01,680 where his friends are getting shot, 342 00:17:01,680 --> 00:17:04,910 she's at risk by her own connections to this network. 343 00:17:04,920 --> 00:17:07,780 Andrew's social network analysis shows that gun crime 344 00:17:07,790 --> 00:17:11,420 is highly localized within social networks. 345 00:17:11,420 --> 00:17:14,190 In one of Chicago's high-crime neighborhoods, 346 00:17:14,190 --> 00:17:18,530 41% of all gun homicides took place in a network 347 00:17:18,530 --> 00:17:22,600 that represented just 4% of the population. 348 00:17:22,600 --> 00:17:24,870 You have a very small percentage of the population 349 00:17:24,870 --> 00:17:26,740 that are responsible for the vast majority 350 00:17:26,740 --> 00:17:28,900 of the violence as victims. 351 00:17:28,910 --> 00:17:32,440 You can use that information to use prevention efforts, 352 00:17:32,440 --> 00:17:34,810 as well as enforcement after its... when needed, 353 00:17:34,810 --> 00:17:36,010 to get those individuals. 354 00:17:36,010 --> 00:17:38,910 And in fact, to save their lives. 355 00:17:38,920 --> 00:17:41,250 But focusing on small social networks 356 00:17:41,250 --> 00:17:45,190 to prevent gun crime also has a down side. 357 00:17:45,190 --> 00:17:48,960 In Chicago, the police department has faced criticism 358 00:17:48,960 --> 00:17:53,130 for tracking people based only on who they know. 359 00:17:53,130 --> 00:17:56,930 But it claims the heat list has a social benefit. 360 00:17:56,930 --> 00:17:59,440 A cop may come knock on your door, 361 00:17:59,440 --> 00:18:02,140 but a social worker would be there, too. 362 00:18:02,140 --> 00:18:03,610 The goal is not to be punitive. 363 00:18:03,610 --> 00:18:05,710 The goal is to try to reduce the chance 364 00:18:05,710 --> 00:18:06,810 that somebody's gonna be 365 00:18:06,810 --> 00:18:08,680 continuing the cycle of violence. 366 00:18:08,680 --> 00:18:12,720 The jury is still out on Chicago's heat list, 367 00:18:12,720 --> 00:18:16,490 but no one expects it to prevent every gun death. 368 00:18:16,490 --> 00:18:20,790 So, how can we protect ourselves from the gun virus? 369 00:18:20,790 --> 00:18:26,800 Should we all go out and buy ourselves a gun? 370 00:18:31,060 --> 00:18:33,560 You've seen it in the movies. 371 00:18:33,560 --> 00:18:36,660 Our hero saves the day with a well-aimed shot. 372 00:18:36,670 --> 00:18:38,800 It's the end of the road for you, Malone. 373 00:18:41,670 --> 00:18:44,700 This is the heart of the gun debate. 374 00:18:44,710 --> 00:18:46,740 Does it take a good guy with a gun 375 00:18:46,740 --> 00:18:49,740 to stop a bad guy with a gun? 376 00:18:49,750 --> 00:18:51,280 I ain't done yet. 377 00:18:54,450 --> 00:18:59,350 Or would it just mean more bullets flying around? 378 00:18:59,350 --> 00:19:03,790 Do guns make us more safe, or less? 379 00:19:06,800 --> 00:19:10,530 Epidemiologist Charlie Branas started out as a paramedic. 380 00:19:10,530 --> 00:19:12,830 On the tough streets of Philadelphia, 381 00:19:12,830 --> 00:19:15,500 he treated many gunshot wounds. 382 00:19:15,500 --> 00:19:19,140 As a paramedic, I was exposed to cases of gun violence, 383 00:19:19,140 --> 00:19:22,310 but it became very frustrating not to be able 384 00:19:22,310 --> 00:19:23,540 to prevent those cases, 385 00:19:23,550 --> 00:19:26,810 to simply see them on a regular basis. 386 00:19:26,820 --> 00:19:29,880 It was here in Philadelphia where the right to bear arms 387 00:19:29,890 --> 00:19:34,090 was added to the U.S. constitution in 1791. 388 00:19:34,090 --> 00:19:37,120 Today, it's reeling from gun violence 389 00:19:37,130 --> 00:19:40,430 with almost five shootings a day. 390 00:19:40,430 --> 00:19:43,400 So, now, Charlie is returning to the crime scenes 391 00:19:43,400 --> 00:19:45,570 he once visited as a paramedic 392 00:19:45,570 --> 00:19:49,240 with the skills of an epidemiologist. 393 00:19:49,240 --> 00:19:52,570 And he's asking one burning question... 394 00:19:52,570 --> 00:19:56,410 Does carrying a gun make you safer? 395 00:19:56,410 --> 00:19:58,950 It is important to begin to think about 396 00:19:58,950 --> 00:20:01,310 whether a gun is protective or perilous, 397 00:20:01,320 --> 00:20:03,820 and if you are in possession of a firearm, 398 00:20:03,820 --> 00:20:07,490 under what conditions will you be able to protect yourself? 399 00:20:07,490 --> 00:20:11,830 His first challenge was how to study this scientifically. 400 00:20:11,830 --> 00:20:14,060 Charlie knew he couldn't hand out guns 401 00:20:14,060 --> 00:20:17,200 and wait to see which subjects got shot. 402 00:20:17,200 --> 00:20:20,670 But epidemiology offers a different approach... 403 00:20:20,670 --> 00:20:23,800 Find people who've contracted a disease 404 00:20:23,810 --> 00:20:27,240 and then work backward to discover how they caught it. 405 00:20:27,240 --> 00:20:29,980 To identify cases of the gun virus, 406 00:20:29,980 --> 00:20:32,150 Charlie got his research team hooked up 407 00:20:32,150 --> 00:20:34,610 with Philadelphia's police department. 408 00:20:37,350 --> 00:20:40,120 We set up, with the city police department, 409 00:20:40,120 --> 00:20:42,660 a system whereby we were notified, 410 00:20:42,660 --> 00:20:44,420 typically on the day of a shooting, 411 00:20:44,430 --> 00:20:47,490 but soon after, within hours. 412 00:20:47,500 --> 00:20:49,530 As the shootings roved in, 413 00:20:49,530 --> 00:20:53,470 the team collected key details about each victim. 414 00:20:53,470 --> 00:20:55,200 Where was he at the time? 415 00:20:55,200 --> 00:20:58,170 To what age group and race did he belong? 416 00:20:58,170 --> 00:21:02,010 Was he under the influence of drugs or alcohol? 417 00:21:02,010 --> 00:21:05,710 And most importantly, was he carrying a gun? 418 00:21:05,710 --> 00:21:10,620 But in epidemiology, you can't pinpoint why a person gets sick 419 00:21:10,620 --> 00:21:14,450 until you compare him to a similar person who hasn't. 420 00:21:14,460 --> 00:21:16,790 So, for every gunshot victim, 421 00:21:16,790 --> 00:21:19,330 Charlie's team had to find a comparable person... 422 00:21:19,330 --> 00:21:23,000 during the past month... who was not shot. 423 00:21:23,000 --> 00:21:26,470 As a case came in, depending on their age, 424 00:21:26,470 --> 00:21:28,700 their race, and their gender, 425 00:21:28,700 --> 00:21:30,900 we called around, through random digit dialing 426 00:21:30,910 --> 00:21:35,110 across the city, to find someone roughly of the same age, 427 00:21:35,110 --> 00:21:37,910 race, and gender, to ask them quickly 428 00:21:37,910 --> 00:21:39,250 about their experiences 429 00:21:39,250 --> 00:21:41,650 at the time of a case and shooting. 430 00:21:41,650 --> 00:21:44,980 And lastly, they asked their interviewees 431 00:21:44,990 --> 00:21:47,590 whether they themselves had been carrying a gun 432 00:21:47,590 --> 00:21:50,260 at the time the crime took place across town. 433 00:21:50,260 --> 00:21:51,960 How old are you? Do you own a gun? 434 00:21:51,960 --> 00:21:54,090 Where were you at 10:00 P.M. last Wednesday? 435 00:21:54,100 --> 00:21:56,430 Were you in possession of a firearm at this time? 436 00:21:56,430 --> 00:22:00,170 For over 2.5 years, Charlie and his team collected data 437 00:22:00,170 --> 00:22:04,440 on almost 3,500 shootings. 438 00:22:04,440 --> 00:22:07,810 They ended up with 677 shooting victims 439 00:22:07,810 --> 00:22:10,980 for whom they had a good comparison group. 440 00:22:10,980 --> 00:22:14,480 Now, Charlie could answer the central question... 441 00:22:14,480 --> 00:22:18,020 Are you less likely to be shot if you're carrying a gun? 442 00:22:19,820 --> 00:22:22,260 We expected to see a protective effect, 443 00:22:22,260 --> 00:22:23,990 and we simply could not find it, 444 00:22:23,990 --> 00:22:26,930 no matter how we analyzed the data. 445 00:22:26,930 --> 00:22:30,960 In fact, Charlie saw exactly the opposite. 446 00:22:30,970 --> 00:22:33,200 Philadelphians were four and a half times 447 00:22:33,200 --> 00:22:35,400 more likely to be shot 448 00:22:35,400 --> 00:22:38,440 if they were in possession of a gun. 449 00:22:38,440 --> 00:22:40,410 One of the things that we hypothesized 450 00:22:40,410 --> 00:22:42,710 from our case-control study was that, 451 00:22:42,710 --> 00:22:45,880 possession of a firearm changed peoples' actions... 452 00:22:45,880 --> 00:22:47,080 Mere possession of it. 453 00:22:47,080 --> 00:22:49,820 And so, that, perhaps, people reacted in ways 454 00:22:49,820 --> 00:22:52,050 they would have otherwise not reacted 455 00:22:52,050 --> 00:22:54,390 had they not had a firearm. 456 00:22:54,390 --> 00:22:58,020 Charlie plans future research to see whether firearm training 457 00:22:58,030 --> 00:23:00,960 could make guns more protective. 458 00:23:00,960 --> 00:23:02,860 But his research on gun possession 459 00:23:02,860 --> 00:23:05,030 sends a simple message... 460 00:23:05,030 --> 00:23:08,640 If you want to lower your chances of being shot, 461 00:23:08,640 --> 00:23:11,740 don't carry a gun. 462 00:23:11,740 --> 00:23:16,210 Is the best way to immunize yourself against the gun virus 463 00:23:16,210 --> 00:23:19,480 not to put a firearm in your hand? 464 00:23:19,480 --> 00:23:23,950 Well, that may not be enough, because science is finding 465 00:23:23,950 --> 00:23:27,720 guns do strange things to our minds. 466 00:23:27,720 --> 00:23:32,760 The mere sight of one can trigger an outburst of violence. 467 00:23:37,100 --> 00:23:39,570 We've all heard it said... 468 00:23:39,570 --> 00:23:44,370 "guns don't kill people. People kill people." 469 00:23:44,370 --> 00:23:47,040 In other words, the gun isn't what matters... 470 00:23:47,040 --> 00:23:50,010 It takes a finger to pull the trigger. 471 00:23:50,010 --> 00:23:54,210 But new research casts doubt on this idea. 472 00:23:54,220 --> 00:23:57,480 Maybe it's not the people who fire them, 473 00:23:57,490 --> 00:24:00,820 but guns alone, that are fueling the epidemic. 474 00:24:05,090 --> 00:24:09,030 Why do people shoot one another? 475 00:24:09,030 --> 00:24:10,530 For over 25 years, 476 00:24:10,530 --> 00:24:13,730 Ohio state university psychologist Brad bushman 477 00:24:13,740 --> 00:24:17,400 has been asking that question. 478 00:24:17,410 --> 00:24:23,010 But recently, he's been asking it in an unusual setting. 479 00:24:23,010 --> 00:24:25,480 This state-of-the-art simulator 480 00:24:25,480 --> 00:24:29,420 was designed to study the behavior of drivers. 481 00:24:29,420 --> 00:24:33,450 But Brad hijacked it to study aggression. 482 00:24:33,460 --> 00:24:35,590 In this experiment, drivers encountered 483 00:24:35,590 --> 00:24:37,690 a number of frustrating events, 484 00:24:37,690 --> 00:24:41,430 such as somebody mimicking their behavior, 485 00:24:41,430 --> 00:24:44,330 somebody cutting them off in traffic, 486 00:24:44,330 --> 00:24:46,330 construction zones. 487 00:24:46,330 --> 00:24:48,970 We all know about road rage, 488 00:24:48,970 --> 00:24:52,240 but Brad wanted to see if he could trigger it 489 00:24:52,240 --> 00:24:54,470 with something seemingly unrelated. 490 00:24:56,010 --> 00:24:59,550 We placed a stimulus object in the passenger's seat. 491 00:24:59,550 --> 00:25:03,180 What we told participants when they got in the car was, 492 00:25:03,180 --> 00:25:04,620 "this car is being used 493 00:25:04,620 --> 00:25:08,190 in a number of different experiments." 494 00:25:08,190 --> 00:25:10,290 All right. And again, I just wanted to apologize. 495 00:25:10,290 --> 00:25:12,430 The other experiment was supposed to put it away, 496 00:25:12,430 --> 00:25:14,530 but they didn't, so you can just ignore that. 497 00:25:14,530 --> 00:25:15,700 Brad and his team 498 00:25:15,700 --> 00:25:18,630 measured how the tennis-racket subjects drove, 499 00:25:18,630 --> 00:25:20,400 how frustrated they got, 500 00:25:20,400 --> 00:25:22,900 whether they broke any traffic laws, 501 00:25:22,900 --> 00:25:26,110 or leaned on their horns. 502 00:25:26,110 --> 00:25:28,340 Nothing unusual happened. 503 00:25:28,340 --> 00:25:32,250 But the tennis racket was just there to set a baseline. 504 00:25:32,250 --> 00:25:34,410 Brad's real question was, what would happen 505 00:25:34,420 --> 00:25:37,420 when a gun was sitting on the passenger's seat. 506 00:25:37,420 --> 00:25:39,990 So, he's breaking the speed limit again. 507 00:25:39,990 --> 00:25:42,190 He's pretty impatient, I think. 508 00:25:42,190 --> 00:25:45,590 Oh, dude. Right in the middle of the road. 509 00:25:45,590 --> 00:25:46,590 - Oh, man. - Wow, over the center. 510 00:25:46,590 --> 00:25:48,760 That's a double yellow line. 511 00:25:48,760 --> 00:25:51,400 Yeah, I think he's really an aggressive driver. 512 00:25:51,400 --> 00:25:56,940 In driver after driver, Brad saw the same thing happening. 513 00:25:56,940 --> 00:25:59,970 What we discovered in this experiment is that, 514 00:25:59,970 --> 00:26:03,540 the mere presence of a gun in the passenger's seat 515 00:26:03,550 --> 00:26:06,350 made drivers more aggressive. 516 00:26:06,350 --> 00:26:10,020 It primes or activates aggressive thoughts in memory. 517 00:26:10,020 --> 00:26:12,750 We call this "the weapons effect." 518 00:26:12,750 --> 00:26:17,420 in a fight, having a gun would give you the upper hand. 519 00:26:17,430 --> 00:26:20,230 So, perhaps, Brad's armed drivers 520 00:26:20,230 --> 00:26:23,730 consciously chose to be more aggressive. 521 00:26:23,730 --> 00:26:27,270 But Brad thinks we may not be so logical... 522 00:26:27,270 --> 00:26:30,400 At least, not according to a second experiment. 523 00:26:32,340 --> 00:26:34,440 Driver behavior's a great laboratory 524 00:26:34,440 --> 00:26:35,880 for studying aggression, 525 00:26:35,880 --> 00:26:37,810 not just in a driving simulator, 526 00:26:37,810 --> 00:26:40,310 but in the real world. 527 00:26:40,320 --> 00:26:44,320 Researchers did an experiment where they had a pickup truck 528 00:26:44,320 --> 00:26:45,920 pull up to an intersection. 529 00:26:45,920 --> 00:26:50,220 Driver remained at the stop for 12 seconds 530 00:26:50,230 --> 00:26:53,160 to see what the motorist trapped behind him would do. 531 00:27:05,010 --> 00:27:06,670 A few honked. 532 00:27:06,670 --> 00:27:11,340 Most sat quietly until they pulled out and went around. 533 00:27:11,350 --> 00:27:15,980 In a second version, the truck blocking the intersection 534 00:27:15,980 --> 00:27:18,550 had a rifle on a gun rack. 535 00:27:34,670 --> 00:27:37,370 What's amazing about this study is that, people do the opposite 536 00:27:37,370 --> 00:27:39,840 of what you would expect. 537 00:27:39,840 --> 00:27:42,240 Motorists were more likely to honk their horn 538 00:27:42,240 --> 00:27:44,210 when there is a gun in the back window 539 00:27:44,210 --> 00:27:45,440 of the pickup truck 540 00:27:45,450 --> 00:27:48,050 than if there is no gun in the back window. 541 00:27:50,290 --> 00:27:52,750 It's an instinctive response, not a logical one. 542 00:27:52,750 --> 00:27:54,850 There's nothing logical about it. 543 00:27:57,890 --> 00:28:02,190 Why does a gun provoke an aggressive response, 544 00:28:02,200 --> 00:28:05,670 even when it's in someone else's possession? 545 00:28:05,670 --> 00:28:11,300 Brad thinks it comes down to the wiring in our brains. 546 00:28:11,310 --> 00:28:14,210 Human beings are very good at identifying 547 00:28:14,210 --> 00:28:17,280 potentially dangerous stimuli in their environment, 548 00:28:17,280 --> 00:28:20,710 such as spiders and snakes. 549 00:28:20,720 --> 00:28:23,350 It's called the "fight-or-flight response," 550 00:28:25,250 --> 00:28:28,420 and it happens faster than we can think. 551 00:28:28,420 --> 00:28:30,720 Brad believes that the sight of a gun 552 00:28:30,730 --> 00:28:34,530 activates that same system. 553 00:28:34,530 --> 00:28:39,400 We've been repeatedly exposed to images of guns and violence 554 00:28:39,400 --> 00:28:41,770 that the link between guns and violence 555 00:28:41,770 --> 00:28:44,400 in the human brain is very strong 556 00:28:44,410 --> 00:28:46,310 because people recognize them 557 00:28:46,310 --> 00:28:49,410 as a source of threat and danger. 558 00:28:49,410 --> 00:28:52,810 In other words, a gun doesn't merely shoot. 559 00:28:52,810 --> 00:28:56,680 It plants the idea of violence in your mind. 560 00:28:56,680 --> 00:28:58,780 And by triggering those feelings, 561 00:28:58,790 --> 00:29:02,150 a gun is actually prompting you to use it. 562 00:29:02,160 --> 00:29:05,160 Of course, it takes a finger to pull the trigger, 563 00:29:05,160 --> 00:29:08,090 but by increasing these aggressive impulses, 564 00:29:08,100 --> 00:29:11,500 the trigger may also be pulling the finger. 565 00:29:14,700 --> 00:29:19,470 Today, there are more than 300 million guns in America 566 00:29:19,470 --> 00:29:23,940 silently triggering our aggressive impulses. 567 00:29:23,950 --> 00:29:26,950 A few of us give in to them. 568 00:29:29,220 --> 00:29:34,350 But if you catch the gun virus, do you have it for life? 569 00:29:34,360 --> 00:29:38,120 One scientist thinks he's found a way to cure it. 570 00:29:40,200 --> 00:29:43,740 Gun violence, whether it's mass shootings 571 00:29:43,740 --> 00:29:47,140 or the ceaseless daily litany of killings, 572 00:29:47,140 --> 00:29:51,450 is almost always committed by one type of person... 573 00:29:51,450 --> 00:29:53,580 Young men. 574 00:29:53,580 --> 00:29:57,290 If we're going to eradicate the gun virus, 575 00:29:57,290 --> 00:30:02,460 we need therapies to target those who have been infected. 576 00:30:02,460 --> 00:30:04,390 Is there any way to cure them? 577 00:30:09,000 --> 00:30:12,100 Neuroscientist Kent Kiehl is trying to understand 578 00:30:12,100 --> 00:30:14,040 the brains of those who kill. 579 00:30:14,040 --> 00:30:15,140 You dialed 9-1-1. 580 00:30:15,140 --> 00:30:16,170 What's the location of your emergency? 581 00:30:16,170 --> 00:30:17,440 Sandy hook elementary school. 582 00:30:17,440 --> 00:30:18,710 I keep hearing shooting. 583 00:30:18,710 --> 00:30:20,240 It's still happening. 584 00:30:20,240 --> 00:30:22,810 I was approached by the parents who had lost their children 585 00:30:22,810 --> 00:30:25,150 at Sandy hook elementary school in that tragedy. 586 00:30:25,150 --> 00:30:27,520 And they asked if there was any science that we could do 587 00:30:27,520 --> 00:30:28,820 that might help us understand 588 00:30:28,820 --> 00:30:31,250 why people might commit such types of crimes, 589 00:30:31,250 --> 00:30:32,420 and how we might be able 590 00:30:32,420 --> 00:30:34,360 to develop better ways of preventing them. 591 00:30:34,360 --> 00:30:38,460 The tragedy of Sandy hook haunts our society. 592 00:30:38,460 --> 00:30:43,660 In just five short minutes, 20 first-graders were murdered, 593 00:30:43,670 --> 00:30:46,070 along with six teachers. 594 00:30:46,070 --> 00:30:51,110 The killer was male, 20, and disturbed... 595 00:30:53,280 --> 00:30:58,250 Not unlike the young juveniles Kent has come to study. 596 00:30:58,250 --> 00:31:00,110 All of these kids that we were working with 597 00:31:00,120 --> 00:31:02,080 were in an ultra-supermax facility... 598 00:31:02,090 --> 00:31:04,650 The highest risk facility in the state of new Mexico... 599 00:31:04,650 --> 00:31:07,560 Because they had committed one or more felonies. 600 00:31:07,560 --> 00:31:09,990 And I'm not talking, you know, simple things. 601 00:31:09,990 --> 00:31:12,390 These are serious multiple felons. 602 00:31:12,400 --> 00:31:14,260 A lot of the time, the crimes that are committed 603 00:31:14,260 --> 00:31:16,860 by these kids use handguns or firearms. 604 00:31:16,870 --> 00:31:19,530 And almost every one of them has had or owns a firearm, 605 00:31:19,540 --> 00:31:22,000 or has acquired one. 606 00:31:22,010 --> 00:31:24,870 It's really something that's just commonplace. 607 00:31:24,870 --> 00:31:28,880 Kent studies the brains of these violent young offenders, 608 00:31:28,880 --> 00:31:33,050 but his subjects can't come to an MRI lab, 609 00:31:33,050 --> 00:31:36,480 so he brings the lab to them. 610 00:31:36,490 --> 00:31:37,720 So, we designed and created 611 00:31:37,720 --> 00:31:39,990 a state-of-the-art mobile MRI system. 612 00:31:39,990 --> 00:31:43,290 We've scanned the brains of over 4,000 inmates, 613 00:31:43,290 --> 00:31:47,900 developed the world's largest repository of youth populations. 614 00:31:47,900 --> 00:31:49,730 Kent is trying to detect patterns 615 00:31:49,730 --> 00:31:50,930 in brain anatomy 616 00:31:50,930 --> 00:31:54,170 that are correlated with violent behavior. 617 00:31:54,170 --> 00:31:57,840 He scanned the brains of 25 incarcerated young men 618 00:31:57,840 --> 00:31:59,670 who had committed murder 619 00:31:59,680 --> 00:32:03,610 and contrasted them with the brains of 150 offenders 620 00:32:03,610 --> 00:32:05,410 who had not. 621 00:32:05,420 --> 00:32:08,880 He looked for differences in areas involved with emotion, 622 00:32:08,890 --> 00:32:12,750 impulse control, and decision-making... 623 00:32:12,760 --> 00:32:15,320 The amygdala, anterior cingulate, 624 00:32:15,330 --> 00:32:17,290 and orbital frontal cortex. 625 00:32:20,930 --> 00:32:24,930 The scans revealed stark differences. 626 00:32:24,930 --> 00:32:27,640 Turns out that, parts of this amygdala 627 00:32:27,640 --> 00:32:30,270 are actually not well-developed in youths that commit homicides, 628 00:32:30,270 --> 00:32:32,040 compared to their peers. 629 00:32:32,040 --> 00:32:33,640 As well, kids that commit homicide 630 00:32:33,640 --> 00:32:36,410 have less orbital frontal cortex. 631 00:32:36,410 --> 00:32:37,710 Parts of the brain that we have found 632 00:32:37,710 --> 00:32:40,050 that are not developed normally, or developed differently, 633 00:32:40,050 --> 00:32:41,250 are actually parts of the brain 634 00:32:41,250 --> 00:32:42,750 that are kind of the last to develop. 635 00:32:42,750 --> 00:32:46,190 They usually don't reach full maturity until age, about, 25. 636 00:32:46,190 --> 00:32:48,960 It appears almost, like, even though they're 15, 16 years old, 637 00:32:48,960 --> 00:32:51,560 their brains might only really be 10, 11 years old. 638 00:32:51,560 --> 00:32:53,890 With 85% accuracy, 639 00:32:53,900 --> 00:32:57,260 Kent could guess which juveniles had committed murder 640 00:32:57,270 --> 00:33:00,330 just by looking at their brain scans. 641 00:33:00,340 --> 00:33:04,340 Do these differences mean some people are incurably violent, 642 00:33:07,110 --> 00:33:08,910 or is there a saving grace 643 00:33:08,910 --> 00:33:11,310 in the brain's capacity to change? 644 00:33:11,310 --> 00:33:13,510 People are only really kind of beginning to understand this, 645 00:33:13,520 --> 00:33:16,450 but the brain continues to change throughout your life. 646 00:33:16,450 --> 00:33:17,620 All the experiences that you have, 647 00:33:17,620 --> 00:33:19,390 they continue to shape and mold the brain. 648 00:33:25,560 --> 00:33:31,100 But most prison experiences are not helpful for inmate's brains. 649 00:33:31,100 --> 00:33:32,830 Unfortunately, in a correctional environment, 650 00:33:32,840 --> 00:33:36,440 there's really no behaviors that get reinforced positively. 651 00:33:36,440 --> 00:33:38,540 If you're quiet and you're good, and you don't do anything, 652 00:33:38,540 --> 00:33:41,010 what happens? Nothing. 653 00:33:41,010 --> 00:33:43,080 The only thing that gets these individuals 654 00:33:43,080 --> 00:33:45,410 any type of social interaction is aggression. 655 00:33:53,260 --> 00:33:56,090 It's a very dangerous environment for everyone. 656 00:33:56,090 --> 00:33:57,630 That's called "compression." 657 00:33:57,630 --> 00:33:59,390 It compresses them into a very limited set 658 00:33:59,400 --> 00:34:00,960 of behavioral things that they do. 659 00:34:04,830 --> 00:34:09,170 The term "compression" comes from diving. 660 00:34:09,170 --> 00:34:11,440 As a diver descends into the depths, 661 00:34:11,440 --> 00:34:13,440 he encounters greater and greater pressure 662 00:34:13,440 --> 00:34:15,110 from the water. 663 00:34:15,110 --> 00:34:19,580 After a while, his body adjusts. 664 00:34:19,580 --> 00:34:21,820 But at this point, returning to the surface 665 00:34:21,820 --> 00:34:24,750 actually becomes dangerous. 666 00:34:24,750 --> 00:34:27,920 Kent thinks it is just as hard for imprisoned kids 667 00:34:27,920 --> 00:34:32,360 to return to positive kinds of interaction. 668 00:34:32,360 --> 00:34:34,400 The diving analogy is a good one because, 669 00:34:34,400 --> 00:34:36,160 you know, you don't just pop right back up to the surface 670 00:34:36,170 --> 00:34:37,160 and you're healthy again. 671 00:34:37,170 --> 00:34:38,670 That can kill you, right? 672 00:34:39,900 --> 00:34:43,070 Kent is now studying kids who've been through 673 00:34:43,070 --> 00:34:47,140 a therapeutic program called "decompression." 674 00:34:47,140 --> 00:34:49,880 It asks social workers and prison guards 675 00:34:49,880 --> 00:34:51,710 to reward good behaviors 676 00:34:51,710 --> 00:34:54,050 instead of just punishing bad ones. 677 00:34:56,990 --> 00:34:58,690 And so, if the kids were good today, 678 00:34:58,690 --> 00:35:00,450 and they talked to someone, and they engaged with someone, 679 00:35:00,460 --> 00:35:02,960 and they didn't get in fights, they'll get some reward. 680 00:35:02,960 --> 00:35:04,020 And they learn, through these 681 00:35:04,030 --> 00:35:06,560 positive-reinforcement strategies, that, 682 00:35:06,560 --> 00:35:10,260 good things can happen to them if they act better. 683 00:35:10,270 --> 00:35:12,970 12 months after decompression therapy, 684 00:35:12,970 --> 00:35:16,340 Kent conducted a second series of scans. 685 00:35:16,340 --> 00:35:21,010 He saw that critical regions had begun to grow and change. 686 00:35:21,010 --> 00:35:23,380 There's an area of the brain that helps to regulate 687 00:35:23,380 --> 00:35:25,510 decision-making and capacity for decision, 688 00:35:25,520 --> 00:35:27,780 and help you understand when you make mistakes, 689 00:35:27,780 --> 00:35:30,220 and that area of the brain is called the "anterior cingulate," 690 00:35:30,220 --> 00:35:32,820 and we are actually seeing an increase in activity there. 691 00:35:32,820 --> 00:35:35,790 These circuits that control or help to regulate your behavior, 692 00:35:35,790 --> 00:35:38,430 regulate your thinking, they are getting better. 693 00:35:38,430 --> 00:35:42,360 Many underage felons are ultimately released 694 00:35:42,370 --> 00:35:44,270 and have to make the dangerous transition 695 00:35:44,270 --> 00:35:46,900 back to a free society. 696 00:35:46,900 --> 00:35:49,600 A group of inmates not treated with decompression 697 00:35:49,610 --> 00:35:53,110 went on to kill 16 more people. 698 00:35:53,110 --> 00:35:58,050 But inmates who received the therapy killed no one. 699 00:35:58,050 --> 00:36:00,510 One of the things that the programs try to teach them 700 00:36:00,520 --> 00:36:02,350 is how not to act impulsively. 701 00:36:02,350 --> 00:36:04,250 Whether that's with the firearm or without, 702 00:36:04,250 --> 00:36:05,850 it's likely to lead to better outcomes 703 00:36:05,860 --> 00:36:07,790 if they don't act impulsively. 704 00:36:07,790 --> 00:36:09,760 Kent may have found a way to cure those 705 00:36:09,760 --> 00:36:13,260 who've been infected by the gun virus. 706 00:36:13,260 --> 00:36:16,500 But this therapy can only reach a select few, 707 00:36:16,500 --> 00:36:19,700 and only after they have already gone to jail. 708 00:36:19,700 --> 00:36:22,940 Now, one young scientist is working on a different way 709 00:36:22,940 --> 00:36:26,170 to solve the epidemic of gun crime... 710 00:36:26,180 --> 00:36:30,310 Fire a different type of gun. 711 00:36:32,520 --> 00:36:36,160 We've seen how the gun virus spreads. 712 00:36:36,160 --> 00:36:39,160 Mass shootings move through the media. 713 00:36:39,160 --> 00:36:42,930 Street violence spreads through social networks. 714 00:36:42,930 --> 00:36:45,070 Holding a gun or seeing one 715 00:36:45,070 --> 00:36:48,970 triggers the urge to commit more violence. 716 00:36:48,970 --> 00:36:51,910 We all want to stop this pandemic. 717 00:36:51,910 --> 00:36:55,810 One man decided to focus on a part of the disease 718 00:36:55,810 --> 00:36:57,680 that has long been overlooked. 719 00:37:01,190 --> 00:37:02,180 Howdy. 720 00:37:02,190 --> 00:37:03,220 Hey, Kai, how are you? 721 00:37:03,220 --> 00:37:05,490 Like many young people in Colorado, 722 00:37:05,490 --> 00:37:09,490 19-year-old Kai Kloepfer grew up at the gun range. 723 00:37:09,490 --> 00:37:11,230 Do you want the shoot the Ar-15 today? 724 00:37:11,230 --> 00:37:12,230 Definitely. I'd love to. 725 00:37:12,230 --> 00:37:13,230 Awesome. 726 00:37:13,230 --> 00:37:14,400 Growing up in Colorado, 727 00:37:14,400 --> 00:37:16,870 firearms were always a part of the culture... 728 00:37:16,870 --> 00:37:18,500 Maybe not as much as, say, Texas, 729 00:37:18,500 --> 00:37:21,470 but they're definitely accepted. 730 00:37:21,470 --> 00:37:26,080 Most high schoolers don't dwell on the problems caused by guns. 731 00:37:26,080 --> 00:37:29,080 Kai was no different, until four years ago, 732 00:37:29,080 --> 00:37:33,050 when gun violence struck just down the road. 733 00:37:33,050 --> 00:37:37,320 315 and 314 for a shooting at century theatres. 734 00:37:37,320 --> 00:37:40,460 We got another person shot in the leg, a female. 735 00:37:40,460 --> 00:37:44,160 I got people running out of the theater. They're shot. 736 00:37:44,160 --> 00:37:47,230 In Aurora, Colorado, the century theatre 737 00:37:47,230 --> 00:37:48,960 became a scene of horrific slaughter 738 00:37:48,970 --> 00:37:52,000 when a young man opened fire. 739 00:37:52,000 --> 00:37:56,310 He killed a dozen people and wounded 70 more. 740 00:37:56,310 --> 00:37:59,910 Like all Americans, Kai was deeply shaken. 741 00:37:59,910 --> 00:38:02,780 But in the dark days that followed, 742 00:38:02,780 --> 00:38:05,510 he began to think about solutions. 743 00:38:05,520 --> 00:38:07,120 At the time, I was looking for a project 744 00:38:07,120 --> 00:38:09,650 that could have some societal impact. 745 00:38:09,650 --> 00:38:11,620 And with the Aurora-theatre shooting, 746 00:38:11,620 --> 00:38:13,660 I realized that I need to create a gun 747 00:38:13,660 --> 00:38:15,930 that only works for certain people. 748 00:38:15,930 --> 00:38:19,330 And so, that's why I'm working on smart-gun technology. 749 00:38:21,900 --> 00:38:24,030 Kai thought that, by designing a gun 750 00:38:24,040 --> 00:38:26,370 that will only fire for its owner, 751 00:38:26,370 --> 00:38:30,740 he might help prevent some acts of mass homicide. 752 00:38:30,740 --> 00:38:34,940 Then, he realized that, out of more than 30,000 gun deaths 753 00:38:34,950 --> 00:38:39,050 each year, two-thirds weren't homicides at all. 754 00:38:39,050 --> 00:38:42,250 There's an even larger problem of suicides 755 00:38:42,250 --> 00:38:45,250 and accidental gun death with misuse of firearms 756 00:38:45,260 --> 00:38:47,060 that almost nobody talks about. 757 00:38:47,060 --> 00:38:49,460 21,000 firearm suicides, 758 00:38:49,460 --> 00:38:51,360 children that, every 30 minutes, 759 00:38:51,360 --> 00:38:53,460 are killed or injured with a firearm. 760 00:38:53,460 --> 00:38:56,070 Kai knew many of these victims were using a gun 761 00:38:56,070 --> 00:38:58,170 that didn't belong to them. 762 00:38:58,170 --> 00:38:59,870 Would these people have died 763 00:38:59,870 --> 00:39:02,840 if the gun had refused to fire for them? 764 00:39:05,840 --> 00:39:09,280 Starting with a $3,000 loan from his parents, 765 00:39:09,280 --> 00:39:13,420 Kai has now invested four years on this project. 766 00:39:13,420 --> 00:39:17,920 He went through an extensive prototyping process 767 00:39:17,920 --> 00:39:20,860 using a 3D printer in his bedroom. 768 00:39:20,860 --> 00:39:21,890 There's a fingerprint sensor 769 00:39:21,890 --> 00:39:23,660 embedded in the grip of the firearm 770 00:39:23,660 --> 00:39:26,000 that captures an image of their fingerprint. 771 00:39:26,000 --> 00:39:29,160 That image is processed and then matched against a list 772 00:39:29,170 --> 00:39:31,900 that's stored on the gun... Encrypted and secure... 773 00:39:31,900 --> 00:39:34,970 Of everyone who's allowed to use that firearm. 774 00:39:34,970 --> 00:39:37,140 Once we have a verified fingerprint, 775 00:39:37,140 --> 00:39:38,710 there's a little motor 776 00:39:38,710 --> 00:39:40,910 that takes signals from the circuit board 777 00:39:40,910 --> 00:39:42,750 and produces physical motion. 778 00:39:42,750 --> 00:39:46,320 We then use this motion to lock and unlock the firearm. 779 00:39:50,050 --> 00:39:52,620 What started as a high-school project 780 00:39:52,620 --> 00:39:55,320 has become a business in the making. 781 00:39:55,330 --> 00:39:59,560 But Kai has an uphill battle to get his prototype to market. 782 00:39:59,560 --> 00:40:03,200 Smartguns are not a new idea. And about 20 years ago, 783 00:40:03,200 --> 00:40:06,000 the government saw that it was an obviously good idea 784 00:40:06,000 --> 00:40:08,700 and decided to just throw a bunch of money at the problem. 785 00:40:08,710 --> 00:40:11,670 They gave out grants to some major firearm manufacturers, 786 00:40:11,680 --> 00:40:13,310 like Smith & Wesson. 787 00:40:13,310 --> 00:40:16,580 For the very first time, a gun manufacturer 788 00:40:16,580 --> 00:40:17,910 will include locking devices 789 00:40:17,920 --> 00:40:21,220 and other safety features, and will develop smartguns 790 00:40:21,220 --> 00:40:23,450 that can be fired only by the adults 791 00:40:23,450 --> 00:40:25,290 who own them. 792 00:40:25,290 --> 00:40:28,790 The smartguns met with fierce resistance. 793 00:40:28,790 --> 00:40:32,360 Gun-advocacy groups claimed their second-amendment rights 794 00:40:32,360 --> 00:40:33,530 were at risk. 795 00:40:33,530 --> 00:40:34,830 Smith & Wesson got boycotted 796 00:40:34,830 --> 00:40:37,870 and almost lost over 40% of their business, 797 00:40:37,870 --> 00:40:39,870 which is substantial for any company. 798 00:40:39,870 --> 00:40:41,940 They basically abandoned the projects and swore, 799 00:40:41,940 --> 00:40:44,240 more or less, never to work on it again. 800 00:40:44,240 --> 00:40:47,440 Before a single smartgun could be sold, 801 00:40:47,450 --> 00:40:49,710 the product was withdrawn. 802 00:40:49,710 --> 00:40:52,110 A lot of the public, especially the gun-owning public, 803 00:40:52,120 --> 00:40:54,880 perceived smartguns as the gun control or, like, 804 00:40:54,890 --> 00:40:56,520 something that's gonna be mandated. 805 00:40:56,520 --> 00:40:58,450 It's not gun control in any way. 806 00:40:58,460 --> 00:41:00,120 It's not external control. 807 00:41:00,120 --> 00:41:01,720 There's no government database. 808 00:41:01,730 --> 00:41:05,430 Kai believes smartguns will help to inoculate some of us 809 00:41:05,430 --> 00:41:08,930 against the virus that claims so many American lives 810 00:41:08,930 --> 00:41:12,000 without compromising second-amendment rights. 811 00:41:12,000 --> 00:41:15,100 With this technology, the owner is still free to do anything 812 00:41:15,110 --> 00:41:17,470 that they judge they should do with a firearm, 813 00:41:17,480 --> 00:41:20,510 but it will stop children from finding guns, 814 00:41:20,510 --> 00:41:22,810 teenagers from using it to commit suicide, 815 00:41:22,810 --> 00:41:26,950 and a solid portion of the over 30,000 gun deaths 816 00:41:26,950 --> 00:41:28,780 that happen every year in the United States. 817 00:41:33,990 --> 00:41:36,190 I might not be able to stop the next psychopath 818 00:41:36,190 --> 00:41:37,460 who walks into a movie theater, 819 00:41:37,460 --> 00:41:40,830 but there are lives that I can save. 820 00:41:40,830 --> 00:41:44,130 Even if we can save one person's life, 821 00:41:44,140 --> 00:41:47,570 that'd make the whole thing worth it. 822 00:41:47,570 --> 00:41:52,140 A smartgun would make a dent in the gun virus, 823 00:41:52,140 --> 00:41:54,310 but only a small one. 824 00:41:54,310 --> 00:41:58,980 In fact, all the solutions are in their early days, 825 00:41:58,980 --> 00:42:03,050 which is strange, considering how dire the situation is. 826 00:42:03,050 --> 00:42:08,290 Guns claim over 30,000 American lives each year. 827 00:42:08,290 --> 00:42:10,760 When Ebola threatened our shores, 828 00:42:10,760 --> 00:42:13,500 the full resources of our public-health community 829 00:42:13,500 --> 00:42:16,300 were called into service. 830 00:42:16,300 --> 00:42:18,630 You know how many people died in the U.S. 831 00:42:18,640 --> 00:42:22,300 From that devastating disease? 832 00:42:22,310 --> 00:42:23,840 Two. 833 00:42:23,840 --> 00:42:27,780 When the United States puts its resources to work, 834 00:42:27,780 --> 00:42:30,080 we have great results. 835 00:42:30,080 --> 00:42:32,410 But in 1996, a federal law 836 00:42:32,420 --> 00:42:35,220 prohibited the centers for disease control 837 00:42:35,220 --> 00:42:40,860 from funding anything that may lead to gun control. 838 00:42:40,860 --> 00:42:43,230 The law has had a chilling effect 839 00:42:43,230 --> 00:42:47,800 on gun-violence research across the country. 840 00:42:47,800 --> 00:42:51,770 I believe in science, and I believe 841 00:42:51,770 --> 00:42:55,170 it's only with the unfettered help of science, 842 00:42:55,170 --> 00:42:58,870 and the answers it provides, that we'll have a hope 843 00:42:58,880 --> 00:43:03,050 of ending this devastating epidemic. 844 00:43:03,100 --> 00:43:07,650 Repair and Synchronization by Easy Subtitles Synchronizer 1.0.0.0 67736

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